A list of resources for learning ML
There's a few things you need to know
- No list of resources will help you if you're not willing to help yourself
- The best way to learn is by building things
Intro
I am Bones, I build AI Projects in my free time. One of the most common questions I get asked on Twitter is where I learned ML from, so here's a rough guide.
If you're new to programming
- I highly recommend checking out the The Coding Train youtube channel by Daniel Shiffman, it's a treasure trove for anyone looking to learn how to code
- Try to learn the programming concepts and not just language syntax
Getting into ML
Start small, my first ml project was a simple genetic algorithm simulation called Smart Rockets
- Here's the coding train video playlist that I followed
- The first 8 videos will walk you through the basics of genetic algorithm. Then you may jump to the actual video that builds the Smart Rockets, or pick something else to work on
- There's also other really cool videos like Ecosystem simulation, check them all out.
Neural Networks
Again take it step-by-step, start with a Perceptron - the fundamental building block for neural networks
- Introduction to Neural Networks by The Coding train
- NN and Backpropagation basics by Andrej Karpathy
LLMs
Other Resources
- Ludwig's Blog - ludwigabap.bearblog.dev/resources-for-ml/
- Here's a small book I've started reading, The Little Book of Deep Learning by François Fleuret - fleuret.org/public/lbdl.pdf
- The Nature of Code book by Daniel Shiffman
This should be enough to get you started :)